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The Future of User Research: To Thine Users Be True (even when they don’t need you)

Sibongile sighed and put her pen and journal down. Today was May 20, 2050. Was she just a nostalgic second cycler—facing another lifetime in the age of 150-year-olds? It was her 70th birthday and her brood of children, grandchildren, partner and ex-partners were all going to be hologramed in from across the world. Her partner worked on Google’s Project Infinity, a project so very confidential that she hadn’t heard from him in a year. Would he make contact today? She had made sure when upgrading her hologram delivery service that it took into account the possibility that Dingane could be orbiting in space while holograming!

She looked wistfully at her pen and paper journal. Completely obsolete now. She had, thanks to her foresight way back in 2016, hoarded a bunch of special pens and paper. But she had to be very, very careful about not showing them to anyone, not even her family. If anyone saw her using these, she would be termed an ‘archaic’ by the USO (USER segmentation organisation), the global organization that decided which segment you fitted into. There were excellent, good, average and very bad segments. The Archaics were part of the very bad segments category. It was considered a crime against humanity to stop the march of technology in any way, including the use of obsolete, non-technology-based artefacts.

A particularly shameful fate for the director of the ‘Being Human – Digitally’ program.

Sibongile often wondered what she made of this world she lived in today, compared to what it was decades ago. She knew one thing for sure: she so missed the ethnographic research she used to do back then in 2016. Experiencing the ‘realness’ of the environment and meeting the ‘users’ in flesh and blood, in spite of all the recruiting and logistics glitches, was simply indescribable. What one understood of the users and their ecosystem from those home and neighbourhood visits had a richness that was quite impossible to describe today.

And those EPIC conferences she had SO loved to attend, where they all came together from across the world to discuss ethnography, users, innovation and new research methods.

It all started to change at EPIC2025, held at the Singularity University. One of the papers to be presented at the conference—‘How We Got Users to Trust Us with Their Deepest Desires and Fears’, co-authored by the Human Connection Team at Ray K Inc., Cupertino, CA—had everyone very intrigued. No one knew of this company called Ray K Inc. A Google search revealed that Ray K Inc. had been recently acquired by the Transnational Group – Unicom and that Ray K Inc.’s core competency was “cutting-edge user research.” More information would be available once the integration of Ray K within Unicom had been completed.

This mystery pulled a major crowed at the Human Connection Team’s session. The largish meeting room was suffocatingly full a good 15 minutes before the session was to start. So commenced a session that would change the course of user research and the EPIC conference itself, beyond anyone’s imagination.

Harshit Illasandro started his presentation by saying that he couldn’t say very much about his company, Ray K, since it was in the process of post-merger integration and strict confidentiality agreements were in place for all employees. But he could talk about the Human Connection team’s cutting-edge research and was going to show us a video to start with.

He opened with a video—it was like nothing we had seen before! The work was for one of the top cosmetic brands in the world, which wanted to research men and women and their deepest desires and fears about ageing and its impact on their lives, especially on their relationships. The research sample was a mind boggling one million users across Europe and North America. And, NO, this was not a quant, it was deep dive ethnographic research consisting of conversations with the users in their homes, over a period of two months. A collective gasp of disbelief spread across the meeting room: Ethnography with one million users…how was this even possible?

The video then showed snippets from many locations, many households. The faces of the users were blurred and voices changed to maintain confidentiality. But even then, it was an unbelievable sight to see the many, many, many researchers across all locations. They were unbelievably skilled too; each seemed, in some very intangible way, to change their entire personality to match the user perfectly within about 20 minutes of the start of the interaction. It felt as if the researcher were a family member. And, strangely enough, not one researcher took any notes. The researcher built incredible rapport with the user, seemed to have an intuition about what the user’s opinions, feelings and preferences about various topics was likely to be. This magical ability to understand the user within minutes built the comfort and trust needed to elicit some very personal and confidential sharing.

Ray K derived unique insights from the research and recommended innovative ideas, not just for a new anti-ageing product, but for a new domain of services. Sibongile, for one, wondered how much time it must have taken to analyse the one million data points and arrive at these final insights and recommendations. Just at that moment, the screen lit up with a project timeline. Two months for the research and one month for analysis and recommendations. ONE month for analyzing one million data points! Impossible!!

The video suddenly paused. Harshit walked to the lectern:

“Are you wondering about the consistently high skill level of our one million researchers? How each of them were able to blend in with the user’s personality? Are you thinking, What training were they given? Are you also wondering about the very short time taken to analyse that HUGE amount of data? Are you then saying, How can this be possible?

All of this was possible for one reason.

Each of the one million user researchers is a humanoid robot.

Very advanced robots at that, fitted with the most cutting-edge emotion predicting and thought decoding algorithms, and the BIG and THICK data analysis, big picture creation and lateral ideation algorithms

Ray K Inc. is the company behind every robot you see in the market today, but white labeled by well-known brands. This research was the first time Ray K did an experiment on its own. That is why Unicom has bought Ray K at a phenomenal price.

All of Unicom’s research will, from this point onwards, be done by our robot researchers. They are super skilled and super cheap.

They are called the Human Connectors.”

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Silence filled the room—a silence so thick that it felt as if no one was even breathing. Sibongile knew at that very moment that her life and world as an ethnographer was coming to an end.

That’s when she made her decision, to cross over to the dark side…of BIG Data and quant research.

But she did feel very sorry for the robot researchers.

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Sibongile had retrained and joined the Government’s MEGA Data section in 2026. The more she immersed herself in her new job, the more horrified she was. ALL this data that was constantly being collected, sliced, analysed; dots were connected, judgements made, data was packaged and sold in different colorful formats to companies around the world. It was sold through a subscription service and depending on the level of subscription a company had, they received more or less detailed data and more or less analysis and insights.

She worked in the subscription and renewal department and the sight of the various ‘packages’ of data that were sent out reminded her of pills that a pharmacy handed out to patients. These ‘packages’ were, like pills intended to help companies change human/user behavior and thought . Advertising from the past seemed harmless compared to the level of manipulation now possible with the recommendations and insights contained in these packages. This data, yes, all the connected data in the world, was used to create filter bubbles and cyber dead ends, hidden paths and short cuts, that users would be deceptively led to take and then believe that they were taking these decisions totally of their own free will.

It was here in the subscriptions and renewal section that she had discovered that the highest level of subscription (cost confidential!) was for the Live Data Streaming service. This service was available for India and China, the strongest economies of the time.

The Live Data Streaming service enabled the subscriber to get access to the continuous data being gathered all the time about every user. This was possible because in both these countries, the population had always been very skilled with technology creation and usage. Now, everyone had technology embedded in them (if they were the digitally rich part of the population) or had the more affordable wearables (if they were the digitally poor). Their immediate environment was also wired and embedded with sensors. Since the USO had replaced Maslow’s Hierarchy of Needs with the Digital Hierarchy of Needs, India and China had embraced this new hierarchy of needs with the aspirational energy of 3 billion beings.

Being embedded with technology, whether internally or externally, was a must have in order to get to digital self-actualization. The population was convinced that to fulfill the higher order digital needs, it was acceptable for the government to constantly receive data from each of them as they went about their daily activities…data about movement, rest, sleep, work, food, relaxation, entertainment, education, love, sex, conflict, shopping, everything. Everyone would, sometime or another, be questioned via the dialogue app or via a voice call, and was required to answer immediately: ‘What did you feel when your friend said she had just got the very latest formless iPhone at $200 less than what you spent?’ ‘Why did you just undelete that email?’ ‘Why did you buy that red top…it’s the tenth one you have bought in the last week!’ If they didn’t answer immediately, access to their favourite sites such as VRTube or GameBook or NewsFeeds or HungerGames 24/7 was suspended.

Based on a monthly evaluation by unknown algorithms, some people were leveled up in the digital hierarchy of needs and so were exposed to new experiences, unique to that level. The hope of being leveled up made everyone a willing participant in the continuous data collection. Compliance was virtually universal.

And THIS data is what was live streamed to the corporations who paid that undisclosed premium. The subscription also came with the entire Big and Thick Sense Making Suite that analysed the live stream data and provided insights.

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Compliance was not absolutely complete. Slowly, Sibongile realized that it was time to end the dictatorship of the algorithms by sabotaging from the inside. Disrupting the algorithms would not be an impossible task…but for how long would that work? The algorithms would be fixed. No, a very different strategy was needed. In losing, there was a win…for her beloved users to be free from being watched and studied all the time.

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Sibongile asked for a special taskforce to get Africa to embrace the digital hierarchy of needs and become human, digitally. She told her boss that she would take this on as part of the ‘Be Good , Do Good—Digitally’ program and hence wasn’t expecting any extra salary or promtion.

It was instantly approved and Sibongile was given charge of Africa.

Originally from South Africa herself, Sibongile decided to start there. She had been in constant touch with all her friends and family back in Durban in spite of having moved to the USA decades ago.

The program got off to a rocking start with all the big multinational corporations outdoing each other in establishing the internet of things and people (IoTP) across south Africa. Wearables were distributed at low or no cost. Open and free connectivity was enhanced through the country. And, of course, the algorithms began to be cutomised for South Africa.

What no one inside the department noticed was the number of South African nationals who became part of the algorithm customisation team. It seemed the most obvious thing to do.

Sibongile’s plan worked perfectly, unsuspected and undetected. From 2028 until today, she had managed to help the meteoric rise of a South African Collaborative Commons. She had been a big fan of Mason and Rifkin, who had said way back in 2016 that we were entering a world beyond markets where we would learn how to live together in an increasingly interdependent global Collaborative Commons. And this paradigm shift was being fuelled by new global connectedness made possible by Big Data and the Internet of Things. Also back then Paul Mason (2015) wondered whether we were on the brink of a paradigm shift where capitalism was transitioning to something totally new. Like Rifkin, he contended that informational technology was making this shift inevitable and ‘has the potential to reshape utterly our familiar notions of work, production and value; and to destroy an economy based on markets and private ownership’. He pointed out that we do actually have the ‘chance to create a more socially just and sustainable global economy’.

THAT is exactly what Sibongile’s covert ops had achieved. The algorithms, while live streaming data from the users across a connected South Africa,to the subscribing MNCs, had also started streaming data back to the users about the possible MNC plans and also about each other. Awareness of the MNC plans and the ability to see that there were likeminded people around the country led to what at first seemed like harmless communities that began to surface across South Africa, experimenting with food collectives and maker studios. But very soon it became a movement that every citizen seemed to align with. By the time the MNCs started to get worried that their consumer insights were not working in their favour—in spite of the very expensive live data streaming subscription—South Africa had become a trailblazer in developing an ecosystem where the entire country consisted of hyper-local communities who were off the grid, produced their own food and 3D printed the products they needed. It was a totally sustainable lifestyle.

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Sibongile’s purpose had been achieved. Her beloved ‘users’ in South Africa didn’t need anyone from outside to research them. They created/produced/designed for their own small communities and they were their own users! They had no use for anything that came from outside their community. There was no user to research.

Now this model was spreading like wild fire around the world. Sibongile had not been able to revive the old practice of user research she had so enjoyed, instead she had ‘freed’ her users from constant surveillance.

In one defeat lay another victory.

And, after all, she was not so sure any more that the very fulfilling, deep and immersive use research she used to do back in 2016 was not what sowed the seeds for the robotic researchers and the live data streaming service.

But now she had made it up to her users for any culpability she may have had…

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Sibongile felt such a big surge of happiness (well, she was being rather naughty… she had switched off her emotion thermostat without permission!) as she now waited for her holographic family to visit…

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Photo 1: Ever-1, a female android developed by the Korea Institute of Industrial Technology, demonstrated to the public on 4 May 2006. The robot is 160cm tall and weighs 50kg.
Photo 2: Repliee Q2, developed by the Ishiguro research team at Osaka University.; photo by BradBeattie, CC BY-SA 3.0.

Apala Lahiri Chavan is the Chief Design and Delivery Officer at Human Factors International. Her passion is to envision how user experience changes across time and space. She has developed a vast array of user research techniques that adapt to diverse cultural and economic environments and specializes in creating breakthrough user experience (UX) strategy. Apala is an award-winning designer (International Audi Design Award 1996). She co-edited the book Innovative Solutions: What Designers Need to Know for Today’s Emerging Markets and her TEDx talk is Three Laws of User Experience. Follow her @FuturistApala